bioRxivBioengineeringPreprint
Consensus Finder web tool to predict stabilizing substitutions in proteins
Abstract
The consensus sequence approach to predicting stabilizing substitutions in proteins rests on the notion that conserved amino acids are more likely to contribute to the stability of a protein fold than non-conserved amino acids. To implement a prediction for a target protein sequence, one finds homologous sequences and aligns them in a multiple sequence alignment. The sequence of the most frequently occurring amino acid at each position is the consensus sequence. Replacement of a rarely occurring amino acid in the target with a frequently occurring amino acid is predicted to be stabilizing. Consensus Finder is an open-source web tool that automates this prediction. This chapter reviews the rationale for the consensus sequence approach and explains the options for fine-tuning this approach using Staphylococcus nuclease A as an example.Competing Interest StatementThe authors have declared no competing interest.View Full Text
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Predicting absolute protein folding stability using generative models
M. Cagiada, S. Ovchinnikov, K. Lindorff-Larsen·bioRxiv·Mar 14, 2024
- Surface residues and non-additive interactions stabilize a consensus homeodomain protein
M. Sternke, K. W. Tripp, D. Barrick·bioRxiv·Apr 19, 2021
- Consensus sequence design as a general strategy to create hyperstable, biologically active proteins
M. Sternke, K. W. Tripp, D. Barrick·bioRxiv·Apr 29, 2019
- A little walk from physical to biological complexity: protein folding and stability
Fabrizio Pucci, Marianne Rooman·bioRxiv·Mar 15, 2016
- Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations
- Best templates outperform homology models in predicting the impact of mutations on protein stability
Marina A. Pak, Dmitry N. Ivankov·BioinformaticsPeer-reviewed·Jul 27, 2022